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A Five-Step Faculty Development Checklist for Artificial Intelligence in Nursing Education

Bibliographic Data

ID22413559
AuthorsLori Lioce (University of Alabama at Birmingham), Tonya Rutherford-Hemming (East Carolina University College of Nursing, Greenville, North Carolina), Tonya Breymier (American Public University System)
Year2026
Pages1-10
Publication date2026-07-16
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Nursing Education (JOURNAL)
Journal identifiersISSN: 0148-4834 • E-ISSN: 1938-2421
PublisherSLACK, Inc. (PUBLISHER)
DOI10.3928/01484834-20260602-02
PMID42447451
OpenAlexW7168259478
LanguageEN
References cited37

BACKGROUND: Artificial intelligence (AI) is increasingly available to faculty and students, yet adoption remains uneven. Faculty report uncertainty about capabilities, limitations, and ethical boundaries, and lack time for integration, while institutions grapple with policy, privacy, and equity concerns. The purpose of this article is to provide a concise, nursing faculty-centered AI development checklist for responsible AI integration in teaching and assessment. METHOD: AI implementation guidance was synthesized into a five-step checklist for faculty AI competency development. RESULTS: The checklist converts exploratory evidence into a logical faculty development plan, emphasizing practical steps that reduce cognitive load, standardize expectations, and support equitable access to enable rapid adoption and consistent implementation for individuals, programs, and institutions. CONCLUSION: With a concise evidence-based checklist, nurses can achieve the benefits of AI while advancing equity and preserving the human-centered core of the nursing profession. This checklist simplifies steps for understanding new technologies, adds to research on competencies, and improves instructional efficiency.

Checklist · Cognition · Equity (law) · Exploratory research · Faculty Development · Higher education · MEDLINE · Nurse education · Artificial Intelligence in Healthcare and Education · Explainable Artificial Intelligence (XAI · Simulation-Based Education in Healthcare

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